How companies are overcoming these top challenges in B2B marketing analytics
Photo by UX Indonesia on Unsplash
Marketing analytics matter in every corner of modern business, but never is that more the case than in B2B operations. Unlike in a B2C sphere, B2B sellers need to proactively go after the accounts they want, and analytics are the best possible tool for doing that.
A reliable, easily understandable data approach can enable everything from the personalized interactions that are so important in account-based marketing strategies, to the business-based trust on which sales rely. Unfortunately, an astounding amount of B2B companies right now are struggling to achieve those outcomes.
To a certain extent, this shouldn’t be surprising. Marketing data is a big mountain to climb, and only 25% of B2B companies report using data to assess client needs weekly, while 9% don’t use data at all. That’s a significant shift compared to the B2C sphere, where around 79% of marketers use analytics to measure content performance, and it highlights one pressing reality – B2B companies are struggling to make full use of marketing analytics right now.
In this article, we’ll consider why that is, and the best ways to change that reality moving forward.
# 1 – Data overload
Photo by Ketut Subiyanto
These days, data comes from everywhere. This is great news for broadening B2B marketing possibilities like account targeting, but performing amidst this influx can feel a lot like trying to climb a mountain during an avalanche.
This is especially true for the high numbers of B2B marketers who don’t yet have the software in place to discern the difference between good, usable data, and the stuff that would be better off in the bin. The result? Hordes of data that will never lead to the true, usable insights necessary to succeed.
Something has to give, and that something is often a data management strategy. Integrated data management software solutions are especially key, as they enable B2B teams to cleanse and validate even high volumes of data, across relevant searches that are completed in seconds.
# 2 – Disparate data sources
B2B marketing activity across a range of online platforms is essential to reaching the widest audience possible, but these options also create data silos that can stop analytical value before it begins. After all, how can you possibly understand audience trends and behaviors if you’re never looking at the whole picture?
You can’t. To do that, it’s essential to streamline data across solutions that provide a unified view. This makes it possible to easily cross-reference marketing trends, sales, and activity. Streamlining data collections and reporting in one place can also be useful for ensuring an automatically clearer, contextualized view from all angles.
# 3 – Complex attributions
Marketing campaigns that are spread across platforms aren’t the only things that risk driving a wedge between B2B data sets. Buyer journeys that include multiple touch points can also make data attributions difficult to achieve, or state with any real certainty.
This means that a B2B company running multiple marketing campaigns may struggle to understand which of those are actually driving sales, and which are reaping far less positive fruits. B2B marketing teams dealing with this issue will also struggle to identify where in the sales funnel potential buyers are turning away, making on-the-ground improvements almost impossible.
Again, software can help here, especially when it comes to solutions that specifically analyze individual touchpoints like social media page views and website click-throughs. Equally, simply seeking client feedback can work wonders. Follow-up emails to happy clients are obviously useful for this purpose, but it may also be worth applying a feedback pop-up window for clients who leave your site at certain points. This will provide much-needed context that makes more sense of raw, unexplainable data.
# 4 – Elusive ROI
Photo by Jonathan Francisca on Unsplash
Many B2B companies also struggle to use data when measuring returns on investment (ROI). This is a fatal setback, as ROI blindness can lead to significant overspends on marketing drives that simply aren’t creating attention.
This is an especially pressing problem for B2B marketers, who may have to spend substantial amounts on complex marketing focuses like white papers and industry-wide surveys. Without the data to back these focuses, or highlight which of them are most worth pursuing, marketing budgets are almost impossible to calibrate.
To some extent, removing data silos and sorting attribution will help here. Aligning analytics directly alongside clear spending KPIs also makes it easier to track specific data-based progress based on goals that can inform, improve, and add intent to B2B marketing moving forward.
Countless companies are facing these top marketing analytics challenges right now. Make sure you aren’t one of them!